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_aHB143.5 _b.H357 2009 |
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_aHandbook of computational econometrics / _cedited by David A. Belsley, Erricos Kontoghiorghes. |
246 | 1 | 1 | _aComputational econometrics |
264 | 1 |
_aChichester, U.K. : _bWiley, _c2009. |
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300 |
_axviii, 496 pages : _billustrations ; _c26 cm |
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336 |
_atext _btxt _2rdacontent |
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337 |
_aunmediated _bn _2rdamedia |
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338 |
_avolume _bnc _2rdacarrier |
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504 | _aIncludes bibliographical references and index. | ||
505 | 0 | 0 |
_g1. _tEconometric software / _rCharles G. Renfro -- _g1.1. _tIntroduction -- _g1.2. _tThe nature of econometric software -- _g1.3. _tThe existing characteristics of econometric software -- _g1.4. _tConclusion -- _g2. _tThe accuracy of econometric software / _rBruce D. McCullough -- _g2.1. _tIntroduction -- _g2.2. _tInaccurate econometric results -- _g2.3. _tEntry-level tests -- _g2.4. _tIntermediate-level tests -- _g2.5. _tConclusions -- _g3. _tHeuristic optimization methods in econometrics / _rManfred Gilli and Peter Winker -- _g3.1. _tTraditional numerical versus heuristic optimization methods -- _g3.2. _tHeuristic optimization -- _g3.3. _tStochastics of the solution -- _g3.4. _tGeneral guidelines for the use of optimization heuristics -- _g3.5. _tSelected applications -- _g3.6. _tConclusions -- _g4. _tAlgorithms for minimax and expected value optimization / _rPanos Parpas and Berc Rustem -- _g4.1. _tIntroduction -- _g4.2. _tAn interior point algorithm -- _g4.3. _tGlobal optimization of polynomial minimax problems -- _g4.4. _tExpected value optimization -- _g4.5. _tEvaluation framework for minimax robust policies and expected value optimization -- _g5. _tNonparametric estimation -- _g5.1. _tIntroduction -- _g5.2. _tDensity estimation -- _g5.3. _tNonparametric regression -- _g5.4. _tNonparametric inferential techniques -- _g6. _tBootstrap hypothesis testing / _rJames G. MacKinnon -- _g6.1. _tIntroduction -- _g6.2. _tBootstrap and Monte Carlo tests -- _g6.3. _tFinite-sample properties of bootstrap tests -- _g6.4. _tDouble bootstrap and fast double bootstrap tests -- _g6.5. _tBootstrap data generating processes -- _g6.6. _tMultiple test statistics -- _g6.7. _tFinite-sample properties of bootstrap supF tests -- _g6.8. _tConclusion -- _g7. _tSimulation-based Bayesian econometric inference: principles and some recent computational advances / _rLennart F. Hoogerheide, Herman K. van Dijk and Rutger D. van Oest -- _g7.1. _tIntroduction -- _g7.2. _tA primer on Bayesian inference -- _g7.3. _tSimulation methods -- _g7.4. _tConcluding remarks -- _g8. _tEconometric analysis with vector autoregressive models / _rHelmut Lutkepohl -- _g8.1. _tIntroduction -- _g8.2. _tVAR processes -- _g8.3. _tEstimation of VAR models -- _g8.4. _tModel specification -- _g8.5. _tModel checking -- _g8.6. _tForecasting -- _g8.7. _tCausality analysis -- _g8.8. _tStructural VARs and impulse response analysis -- _g8.9. _tConclusions and extensions -- _g9. _tStatistical signal extraction and filtering: a partial survey / _rD. Stephen G. Pollock -- _g9.1. _tIntroduction: the semantics of filtering -- _g9.2. _tLinear and circular convolutions -- _g9.3. _tLocal polynomial regression -- _g9.4. _tThe concepts of the frequency domain -- _g9.5. _tThe classical Wiener - Kolmogorov theory -- _g9.6. _tMatrix formulations -- _g9.7. _tWiener - Kolmogorov filtering of short stationary sequences -- _g9.8. _tFiltering nonstationary sequences -- _g9.9. _tFiltering in the frequency domain -- _g9.10. _tStructural time-series models -- _g9.11. _tThe Kalman filter and the smoothing algorithm -- _g10. _tConcepts of and tools for nonlinear time-series modelling / _rAlessandra Amendola and Christian Francq -- _g10.1. _tIntroduction -- _g10.2. _tNonlinear data generating processes and linear models -- _g10.3. _tTesting linearity -- _g10.4. _tProbabilistic tools -- _g10.5. _tIdentification, estimation and model adequacy checking -- _g10.6. _tForecasting with nonlinear models -- _g10.7. _tAlgorithmic aspects -- _g10.8. _tConclusion -- _g11. _tNetwork economics / _rAnna Nagurney -- _g11.1. _tIntroduction -- _g11.2. _tVariational inequalities -- _g11.3. _tTransportation networks: user optimization versus system optimization -- _g11.4. _tSpatial price equilibria -- _g11.5. _tGeneral economic equilibrium -- _g11.6. _tOligopolistic market equilibria -- _g11.7. _tVariational inequalities and projected dynamical systems -- _g11.8. _tDynamic transportation networks -- _g11.9. _tSupernetworks: applications to telecommuting decision making and teleshopping decision making -- _g11.10. _tSupply chain networks and other applications. |
520 | _a"Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels"--Provided by publisher. | ||
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_aEconometrics _xComputer programs _9769759 |
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_aEconomics _xStatistical methods. _9316971 |
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_aEconometrics _xData processing _9779799 |
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700 | 1 |
_aBelsley, David A., _eeditor. _91075646 |
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700 | 1 |
_aKontoghiorghes, Erricos John, _eeditor. _91075647 |
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